A review of battery SOC estimation based on equivalent circuit models

The performance and safety of electric vehicles are heavily dependent on battery state; thus, accurately predicting the state of charge (SOC) within battery management systems (BMS) is critical. Due to the complex characteristics of lithium-ion batteries, SOC cannot be directly measured, making precise estimation essential for enhancing battery performance and longevity. This review summarizes recent advancements in SOC estimation techniques based on equivalent circuit models (ECM) and outlines future directions. ECM-based SOC estimation offers advantages such as simplicity, strong applicability, real-time monitoring, robustness, and rapid response. Future developments will focus on improving model accuracy, integrating multiple models, and incorporating artificial intelligence algorithms, including neural networks and deep learning. As networked and intelligent technologies evolve, SOC estimation will become more integrated and automated, enabling BMS to more accurately predict SOC through cloud data analysis and machine learning, thereby advancing electric vehicle battery technology.